Ooid Cortical Stratigraphy Reveals Common Histories of Individual Co-occurring Sedimentary Grains

Ooids are a common type of carbonate sand grain that form through a combination of constructive and destructive mechanisms: growth via precipitation and diminution via physical abrasion. Because growth and abrasion obey distinct morphometric rules, we developed an approach to quantitatively constrain the history of growth and abrasion of individual ooid grains using the record of evolving particle shape preserved by their cortical layers. We designed a model to simulate >10⁶ possible growth‐abrasion histories for each pair of cortical layer bounding surfaces in an individual ooid. Estimates for the durations of growth and abrasion of each cortical layer were obtained by identifying the simulated history that best fit the observed particle shape. We applied this approach to thin sections of “modern” lacustrine ooids collected from several locations in the Great Salt Lake (GSL), UT, to assess the spatial and temporal variability of environmental conditions from the perspective of individual grains within a single deposit. We found that GSL ooids do not all share the same histories: Clustering ooid histories by a Fréchet distance metric revealed commonalities between grains found together locally within a deposit but distinct differences between subpopulations shared among localities across the GSL. These results support the tacit view that carbonate sedimentary grains found together in the environment do reflect a common history of sediment transport. This general approach to invert ooid cortical stratigraphy can be applied to characterize environmental variability over <1,000 year timescales in both marine and lacustrine ooid grainstones of any geologic age

A Mechanism-Based Approach to Mitigating Harms from Persuasive Generative AI

Recent generative AI systems have demonstrated more advanced persuasive capabilities and are increasingly permeating areas of life where they can influence decision-making. Generative AI presents a new risk profile of persuasion due the opportunity for reciprocal exchange and prolonged interactions. This has led to growing concerns about harms from AI persuasion and how they can be mitigated, highlighting the need for a systematic study of AI persuasion. The current definitions of AI persuasion are unclear and related harms are insufficiently studied. Existing harm mitigation approaches prioritise harms from the outcome of persuasion over harms from the process of persuasion. In this paper, we lay the groundwork for the systematic study of AI persuasion. We first put forward definitions of persuasive generative AI. We distinguish between rationally persuasive generative AI, which relies on providing relevant facts, sound reasoning, or other forms of trustworthy evidence, and manipulative generative AI, which relies on taking advantage of cognitive biases and heuristics or misrepresenting information. We also put forward a map of harms from AI persuasion, including definitions and examples of economic, physical, environmental, psychological, sociocultural, political, privacy, and autonomy harm. We then introduce a map of mechanisms that contribute to harmful persuasion. Lastly, we provide an overview of approaches that can be used to mitigate against process harms of persuasion, including prompt engineering for manipulation classification and red teaming. Future work will operationalise these mitigations and study the interaction between different types of mechanisms of persuasion

Systems-Based Analysis of the \u3cem\u3eSarcocystis neurona\u3c/em\u3e Genome Identifies Pathways That Contribute to a Heteroxenous Life Cycle

Sarcocystis neurona is a member of the coccidia, a clade of single-celled parasites of medical and veterinary importance including Eimeria, Sarcocystis, Neospora, and Toxoplasma. Unlike Eimeria, a single-host enteric pathogen, Sarcocystis, Neospora, and Toxoplasma are two-host parasites that infect and produce infectious tissue cysts in a wide range of intermediate hosts. As a genus, Sarcocystis is one of the most successful protozoan parasites; all vertebrates, including birds, reptiles, fish, and mammals are hosts to at least one Sarcocystis species. Here we sequenced Sarcocystis neurona, the causal agent of fatal equine protozoal myeloencephalitis. The S. neurona genome is 127 Mbp, more than twice the size of other sequenced coccidian genomes. Comparative analyses identified conservation of the invasion machinery among the coccidia. However, many dense-granule and rhoptry kinase genes, responsible for altering host effector pathways in Toxoplasma and Neospora, are absent from S. neurona. Further, S. neurona has a divergent repertoire of SRS proteins, previously implicated in tissue cyst formation in Toxoplasma. Systems-based analyses identified a series of metabolic innovations, including the ability to exploit alternative sources of energy. Finally, we present an S. neurona model detailing conserved molecular innovations that promote the transition from a purely enteric lifestyle (Eimeria) to a heteroxenous parasite capable of infecting a wide range of intermediate hosts. IMPORTANCE Sarcocystis neurona is a member of the coccidia, a clade of single-celled apicomplexan parasites responsible for major economic and health care burdens worldwide. A cousin of Plasmodium, Cryptosporidium, Theileria, and Eimeria, Sarcocystis is one of the most successful parasite genera; it is capable of infecting all vertebrates (fish, reptiles, birds, and mammals—including humans). The past decade has witnessed an increasing number of human outbreaks of clinical significance associated with acute sarcocystosis. Among Sarcocystis species, S. neurona has a wide host range and causes fatal encephalitis in horses, marine mammals, and several other mammals. To provide insights into the transition from a purely enteric parasite (e.g., Eimeria) to one that forms tissue cysts (Toxoplasma), we present the first genome sequence of S. neurona. Comparisons with other coccidian genomes highlight the molecular innovations that drive its distinct life cycle strategies

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Ultra-rare genetic variation in common epilepsies: a case-control sequencing study

BACKGROUND:Despite progress in understanding the genetics of rare epilepsies, the more common epilepsies have proven less amenable to traditional gene-discovery analyses. We aimed to assess the contribution of ultra-rare genetic variation to common epilepsies. METHODS:We did a case-control sequencing study with exome sequence data from unrelated individuals clinically evaluated for one of the two most common epilepsy syndromes: familial genetic generalised epilepsy, or familial or sporadic non-acquired focal epilepsy. Individuals of any age were recruited between Nov 26, 2007, and Aug 2, 2013, through the multicentre Epilepsy Phenome/Genome Project and Epi4K collaborations, and samples were sequenced at the Institute for Genomic Medicine (New York, USA) between Feb 6, 2013, and Aug 18, 2015. To identify epilepsy risk signals, we tested all protein-coding genes for an excess of ultra-rare genetic variation among the cases, compared with control samples with no known epilepsy or epilepsy comorbidity sequenced through unrelated studies. FINDINGS:We separately compared the sequence data from 640 individuals with familial genetic generalised epilepsy and 525 individuals with familial non-acquired focal epilepsy to the same group of 3877 controls, and found significantly higher rates of ultra-rare deleterious variation in genes established as causative for dominant epilepsy disorders (familial genetic generalised epilepsy: odd ratio [OR] 2·3, 95% CI 1·7-3·2, p=9·1 × 10-8; familial non-acquired focal epilepsy 3·6, 2·7-4·9, p=1·1 × 10-17). Comparison of an additional cohort of 662 individuals with sporadic non-acquired focal epilepsy to controls did not identify study-wide significant signals. For the individuals with familial non-acquired focal epilepsy, we found that five known epilepsy genes ranked as the top five genes enriched for ultra-rare deleterious variation. After accounting for the control carrier rate, we estimate that these five genes contribute to the risk of epilepsy in approximately 8% of individuals with familial non-acquired focal epilepsy. Our analyses showed that no individual gene was significantly associated with familial genetic generalised epilepsy; however, known epilepsy genes had lower p values relative to the rest of the protein-coding genes (p=5·8 × 10-8) that were lower than expected from a random sampling of genes. INTERPRETATION:We identified excess ultra-rare variation in known epilepsy genes, which establishes a clear connection between the genetics of common and rare, severe epilepsies, and shows that the variants responsible for epilepsy risk are exceptionally rare in the general population. Our results suggest that the emerging paradigm of targeting of treatments to the genetic cause in rare devastating epilepsies might also extend to a proportion of common epilepsies. These findings might allow clinicians to broadly explain the cause of these syndromes to patients, and lay the foundation for possible precision treatments in the future. FUNDING:National Institute of Neurological Disorders and Stroke (NINDS), and Epilepsy Research UK

How many observations is one generic worth?

Generic language (e.g., “Birds fly”) conveys generalizationsabout categories and is essential for learning beyond our directexperience. The meaning of generic language is notoriouslyhard to specify, however (e.g., penguins don’t fly). Tessler andGoodman (2019b) proposed a model for generics that is math-ematically equivalent to Bayesian belief-updating based on asingle pedagogical example, suggesting a deep connection be-tween learning from experience and learning from language.Relatedly, Csibra and Shamsudheen (2015) argue that genericsare inherently pedagogical, understood by infants as referringto a member of a kind. In two experiments with adults, wequantify the exchange-rate between generics and observationsby relating their belief-updating capacity, varying both thenumber of observations and whether they are presented ped-agogically or incidentally. We find generics convey strongergeneralizations than single pedagogical observations (Expt. 1),even when the property is explicitly demarcated (Expt. 2). Wesuggest revisions to the vague quantifier model of generics thatwould allow it to accommodate this intriguing exchange-rate

How many observations is one generic worth?

Generic language (e.g., “Birds fly”) conveys generalizations about categories and is essential for learning beyond our direct experience. The meaning of generic language is notoriously hard to specify, however (e.g., penguins don’t fly). Tessler and Goodman (2019) proposed a model for generics that is mathematically equivalent to Bayesian belief-updating based on a single pedagogical example, suggesting a deep connection be- tween learning from experience and learning from language. Relatedly, Csibra and Shamsudheen (2015) argue that generics are inherently pedagogical, understood by infants as referring to a member of a kind. In two experiments with adults, we quantify the exchange-rate between generics and observations by relating their belief-updating capacity, varying both the number of observations and whether they are presented pedagogically or incidentally. We find generics convey stronger generalizations than single pedagogical observations (Expt. 1), even when the property is explicitly demarcated (Expt. 2). We suggest revisions to the vague quantifier model of generics that would allow it to accommodate this intriguing exchange-rate.</p

How many observations is one generic worth?

Generic language (e.g., “Birds fly”) conveys generalizations about categories and is essential for learning beyond our direct experience. The meaning of generic language is notoriously hard to specify, however (e.g., penguins don’t fly). Tessler and Goodman (2019) proposed a model for generics that is mathematically equivalent to Bayesian belief-updating based on a single pedagogical example, suggesting a deep connection be- tween learning from experience and learning from language. Relatedly, Csibra and Shamsudheen (2015) argue that generics are inherently pedagogical, understood by infants as referring to a member of a kind. In two experiments with adults, we quantify the exchange-rate between generics and observations by relating their belief-updating capacity, varying both the number of observations and whether they are presented pedagogically or incidentally. We find generics convey stronger generalizations than single pedagogical observations (Expt. 1), even when the property is explicitly demarcated (Expt. 2). We suggest revisions to the vague quantifier model of generics that would allow it to accommodate this intriguing exchange-rate

Ooid Cortical Stratigraphy Reveals Common Histories of Individual Co-occurring Sedimentary Grains

Ooids are a common type of carbonate sand grain that form through a combination of constructive and destructive mechanisms: growth via precipitation and diminution via physical abrasion. Because growth and abrasion obey distinct morphometric rules, we developed an approach to quantitatively constrain the history of growth and abrasion of individual ooid grains using the record of evolving particle shape preserved by their cortical layers. We designed a model to simulate >10⁶ possible growth‐abrasion histories for each pair of cortical layer bounding surfaces in an individual ooid. Estimates for the durations of growth and abrasion of each cortical layer were obtained by identifying the simulated history that best fit the observed particle shape. We applied this approach to thin sections of “modern” lacustrine ooids collected from several locations in the Great Salt Lake (GSL), UT, to assess the spatial and temporal variability of environmental conditions from the perspective of individual grains within a single deposit. We found that GSL ooids do not all share the same histories: Clustering ooid histories by a Fréchet distance metric revealed commonalities between grains found together locally within a deposit but distinct differences between subpopulations shared among localities across the GSL. These results support the tacit view that carbonate sedimentary grains found together in the environment do reflect a common history of sediment transport. This general approach to invert ooid cortical stratigraphy can be applied to characterize environmental variability over <1,000 year timescales in both marine and lacustrine ooid grainstones of any geologic age